Robot Position Reckoning with Kalman Filter and Range Sensing
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Solution Overview
Problem
Conventional cleaning robots face inefficiencies in path navigation and position accuracy, particularly when unintentionally moved or 'kidnapped,' leading to incomplete cleaning and increased energy consumption.
Innovation Solution
A method and apparatus utilizing dead-reckoning and range sensing to determine the position of a moving robot, incorporating a Kalman filter to predict and correct its position, and a relocation mechanism to reset the position when it falls outside a calculated effective area.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If dead-reckoning is used to determine position variation, then navigation efficiency is improved, but position accuracy deteriorates due to error accumulation
Solution Approach 1:
The patent combines dead-reckoning (which provides continuous position updates and high navigation efficiency) with range sensing to fixed positions (which provides absolute position references) to create a hybrid positioning system. The Kalman filter merges these two position sources, using the dead-reckoning position variation with the range-sensed absolute position to calculate an optimized current position, thereby resolving the contradiction between navigation efficiency and position accuracy.
Solution Approach 2:
The system implements feedback by continuously monitoring the robot's position through both dead-reckoning and range sensing, comparing the calculated position with expected positions within the effective area, and correcting position errors when discrepancies are detected. This feedback loop maintains position accuracy while preserving the navigation efficiency of dead-reckoning.
2Productivity
If the robot moves through optimal paths based on position reckoning, then cleaning coverage is improved, but energy consumption increases due to frequent position corrections
Solution Approach 1:
The patent applies partial action by using range sensing not continuously but selectively - primarily when the robot enters the effective area of fixed transceivers or when position accuracy needs verification. This partial use of range sensing provides sufficient position correction to maintain cleaning coverage while avoiding excessive energy consumption from continuous sensor operation and frequent repositioning.
3Measurement precision
If the robot resets position after kidnapping, then position accuracy is improved, but navigation efficiency deteriorates due to relocation overhead
Solution Approach 1:
The system performs preliminary action by continuously maintaining range sensing to fixed positions active and ready, so that when kidnapping is detected (position discrepancy identified), the robot can immediately use the pre-established range measurement data to reset its position without requiring time-consuming re-surveying or complex relocation procedures. This preliminary preparation of position reference data enables rapid position recovery.
Data Source
AI summary
A method and apparatus for reckoning a position of a moving robot using dead-reckoning and range sensing. The method includes performing dead-reckoning to determine a variation state in accordance with motion of the moving robot, calculating an absolute position of the moving robot by sensing a distance between the moving robot and at least one fixed position, predicting an optimized current position of the moving robot using the variation state and the absolute position, determining whether the optimized current position is within a specified effective area, and correcting the optimized current position in accordance with the determined result.